bu11: -1; bu12: 0.5; by1: 1; by2: 0.5; b0 around 0.4; b11 around -0.2; a11 around 0.2
4 latent models (Rasch, 2PL, GPCM, GRM)
Conditions
2 chains with 5000 iterations (2000 warmup)
Outcome: bias (Estimate - True value). Zero = no bias.
Here, I only used the measurement model with covariates to see if the different priors might address overestimated factor loadings.
Using lognormal priors for factor loadings, the estimates seem to be more stable around 0.